no longer using relative import (but using yucky code duplication)

tutorials/examples/train_hypergrid_multinode.py

@@ -37,7 +37,7 @@
 from gfn.modules import DiscretePolicyEstimator, ScalarEstimator
 from gfn.utils.common import set_seed
 from gfn.utils.modules import DiscreteUniform, NeuralNet, Tabular
-from .train_hypergrid import validate_hypergrid
+from gfn.utils.training import validate
 
 DEFAULT_SEED = 4444
 
@@ -358,6 +358,37 @@ def main(args):  # noqa: C901
     return validation_info["l1_dist"]
 
 
+def validate_hypergrid(
+    env,
+    gflownet,
+    n_validation_samples,
+    visited_terminating_states,
+    discovered_modes,
+):
+    validation_info = validate(  # Standard validation shared across envs.
+        env,
+        gflownet,
+        n_validation_samples,
+        visited_terminating_states,
+    )
+
+    # Add the mode counting metric.
+    states, scale = visited_terminating_states.tensor, env.scale_factor
+
+    normalized_states = ((states * scale) - (scale / 2) * (env.height - 1)).abs()
+
+    modes = torch.all(
+        (normalized_states > (0.3 * scale) * (env.height - 1))
+        & (normalized_states <= (0.4 * scale) * (env.height - 1)),
+        dim=-1,
+    )
+    modes_found = set([tuple(s.tolist()) for s in states[modes.bool()]])
+    discovered_modes.update(modes_found)
+    validation_info["n_modes_found"] = len(discovered_modes)
+
+    return validation_info, discovered_modes
+
+
 if __name__ == "__main__":
     parser = ArgumentParser()